心血管评估的综合社会环境风险评分:一个可解释的机器学习方法
Zhuo Chen1, Jean-Eudes Dazard1, Pedro Rafael Vieira de Oliveira Salerno1
1Herman K Hellerstein Professor of Cardiovascular Research, Director, Cardiovascular Research Institute, Harrington Heart and Vascular Institute, University Hospitals, and School of Medicine, Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, United States.
American journal of preventive cardiology
|April 9, 2025
概括
一个新的社会环境 (SE) 心血管风险评分有效预测主要不良心血管事件 (MACE),突出了收入和保险等因素对心脏健康的影响.
科学领域:
- 心脏病学 心脏病学
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
背景情况:
- 心血管疾病 (CVD) 是全球主要的死亡原因.
- 社会环境因素显著影响心血管疾病发病率和死亡率.
- 了解这些因素对于改善风险评估和干预至关重要.
研究的目的:
- 开发和评估一个复合的社会环境 (SE) 心血管风险评分.
- 评估其对主要不良心血管事件 (MACE) 的预测能力.
- 将传统和新的社会环境风险因素纳入心血管风险评估.
主要方法:
- 使用生存随机森林 (RSF) 模型创建SE心血管风险评分.
- 从CLARIFY注册表 (62,438名患者) 中使用了22个人口普查通道级别变量.
- 考克斯比例危险和夏普利添加式解释 (SHAP) 模型用于验证和变量重要性.
主要成果:
- 这项研究包括了62,438名患有高血压和糖尿病等常见并发症的人.
- SE-MACE风险得分与MACE (HR,1.21 [95% CI,1.11-1.32]) 存在强烈的关联,独立于临床因素和CAC得分.
- 重要预测因素包括吸烟率,保险状况和家庭收入中位数,在SE-MACE分数四分位数中观察到明显的风险分层.
结论:
- SE-MACE风险评分有效地将社会环境决定因素纳入心血管风险预测中.
- 它确定了MACE风险较高的个体,支持整体评估框架.
- 建议在多种不同人群中进一步验证.
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